The dotCMS MCP (Model Context Protocol) Server enables AI assistants to interact directly with dotCMS content management capabilities. Built with xmcp, this server provides sandbox-isolated code execution for exploring the dotCMS REST API specification and executing authenticated API calls.

When to Use It:#

• Building AI-powered content management workflows
• Automating content creation and publishing processes
• Creating intelligent content discovery and search experiences
• Developing AI assistants that need to understand your content structure
• Implementing automated content operations and bulk updates

Key Benefits:#

• Conversational Content Management: Ask AI to create, edit, and publish content using natural language instead of navigating through admin interfaces
• Intelligent Content Discovery: Let AI understand your content structure and help you find, organize, and manage content across your site
• Automated Publishing Workflows: Have AI handle content approval, publishing, and archiving based on your business rules
• Smart Content Creation: Generate content that follows your existing content types and field requirements automatically
• Bulk Content Operations: Process multiple pieces of content at once through simple AI conversations
• Developer Productivity: Generate code components, forms, and integrations based on your actual dotCMS content structure

Prerequisites & Setup#

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Get a dotCMS Environment#

Version Compatibility#

• Recommended: dotCMS Evergreen
• Minimum: dotCMS v24.4
• Best Experience: Latest Evergreen release

Environment Setup#

For Production Use:

• ☁️ Cloud hosting options - managed solutions with SLA
• 🛠️ Self-hosted options - deploy on your infrastructure

For Testing & Development:

• 🧑🏻‍💻 dotCMS demo site - perfect for trying out the MCP server
• 📘 Learn how to use the demo site

For Local Development:

• 🐳 Docker setup guide
• 💻 Local installation guide

Create a dotCMS API Token#

[!WARNING] This MCP server requires an API token with write permissions for Content Types, Content, and Workflows. Only use tokens with the minimum required permissions and secure them properly.

This integration requires an API Token with content management permissions:

1. Go to the dotCMS admin panel
2. Click on System > Users
3. Select the user (with proper permissions) you want to create the API Token for
4. Go to API Access Key and generate a new key

For detailed instructions, please refer to the dotCMS API Documentation.

Configuration#

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Before setting up the MCP server, you need these environment variables to connect to your dotCMS instance:

Environment Variables#

Quickstart#

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Get up and running with the dotCMS MCP Server in minutes.

The server runs on both Node.js (≥20) and Bun — the correct sandbox implementation is selected automatically at runtime.

[!NOTE] This version is currently in beta. Once stable, replace @dotcms/mcp-server@beta with @dotcms/mcp-server in the examples below.

Claude Desktop Setup#

Add the MCP server to your Claude Desktop configuration file. The configuration file location varies by operating system:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Using npx (Node.js):

{
    "mcpServers": {
        "dotcms": {
            "command": "npx",
            "args": ["-y", "@dotcms/mcp-server@beta"],
            "env": {
                "DOTCMS_URL": "https://your-dotcms-instance.com",
                "AUTH_TOKEN": "your-api-token"
            }
        }
    }
}

Using bunx (Bun):

{
    "mcpServers": {
        "dotcms": {
            "command": "bunx",
            "args": ["@dotcms/mcp-server@beta"],
            "env": {
                "DOTCMS_URL": "https://your-dotcms-instance.com",
                "AUTH_TOKEN": "your-api-token"
            }
        }
    }
}

Cursor IDE Setup#

Add the MCP server to your Cursor configuration. Open Cursor Settings and navigate to "Features" > "Model Context Protocol" or create/edit the configuration file:

Using npx (Node.js):

{
    "mcpServers": {
        "dotcms": {
            "command": "npx",
            "args": ["-y", "@dotcms/mcp-server@beta"],
            "env": {
                "DOTCMS_URL": "https://your-dotcms-instance.com",
                "AUTH_TOKEN": "your-api-token"
            }
        }
    }
}

Using bunx (Bun):

{
    "mcpServers": {
        "dotcms": {
            "command": "bunx",
            "args": ["@dotcms/mcp-server@beta"],
            "env": {
                "DOTCMS_URL": "https://your-dotcms-instance.com",
                "AUTH_TOKEN": "your-api-token"
            }
        }
    }
}

Start Using#

1. Restart your AI assistant (Claude Desktop or Cursor)
2. Start creating: Ask the AI to create content, manage workflows, or generate code

Example interactions:

You: "Create a new blog post about AI in content management"
AI: [Searches the API spec, then executes the appropriate API calls]

You: "Show me all my content types"
AI: [Discovers and displays your content schemas]

You: "Generate a React component for my Product content type"
AI: [Analyzes your Product fields and generates a complete component]

Available Tools#

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The dotCMS MCP Server provides tools that enable comprehensive content management through AI:

Search#

Tool: search

Purpose: Explore the dotCMS REST API specification using JavaScript code that runs in an isolated sandbox.

The spec global contains the full dereferenced OpenAPI spec with paths object.

// List all available endpoint paths
return Object.keys(spec.paths)

// Find endpoints related to content types
return Object.entries(spec.paths)
  .filter(([path]) => path.includes('contenttype'))
  .map(([path, methods]) => ({ path, methods: Object.keys(methods) }))

Execute#

Tool: execute

Purpose: Execute authenticated API calls against your dotCMS instance using JavaScript code in an isolated sandbox.

// List content types
const result = await api.request({ path: '/api/v1/contenttype' })
return result

// Search content with Elasticsearch
const result = await api.request({
  method: 'POST',
  path: '/api/v1/es/search',
  body: { query: 'contentType:webPageContent +languageId:1' }
})
return pick(result.contentlets, ['identifier', 'title', 'modDate'])

Helper utilities available: pick(arr, fields), table(arr), count(arr, field), sum(arr, field), first(arr, n)

Download Assets#

Tool: download_assets

Purpose: Download a dotCMS asset folder to the MCP server filesystem while returning only a small JSON manifest.

{
    "path": "/application/themes/travel",
    "dest": "/absolute/local/path/themes/travel",
    "recursive": true,
    "overwrite": "skip",
    "include": "*.vtl,*.scss"
}

The tool enumerates file assets with /api/content/_search, downloads bytes with /api/v2/assets/{identifier} through the server-side runtime, writes files under dest, and preserves relative folder structure. File bytes are not returned to the model.

Upload Assets#

Tool: upload_assets

Purpose: Upload a local directory to dotCMS file assets using /api/v2/assets/publish or /api/v2/assets/save.

{
    "src": "/absolute/local/path/themes/travel",
    "dest": "//demo.dotcms.com/application/themes/travel",
    "include": "*.vtl,*.scss",
    "publish": true,
    "verify": true
}

The upload destination must be host-qualified. When publish and verify are true, the tool checks live status with /api/v1/content/{identifier} and retries publish for files that did not become live.

Pre-loaded Instance Context#

Both search and execute automatically pre-load a minimal snapshot of the connected dotCMS instance and inject it into the sandbox as globals. The AI does not need to make discovery calls before doing work.

Available globals in both tools:

// No round trip needed to find a content type by variable
const blog = contentTypes.find(c => c.variable === 'Blog')

// Resolve the default site without an extra call
const defaultSite = sites.find(s => s.isDefault)

How it works

• Context is fetched the first time a tool is invoked in an MCP session and cached in memory for 5 minutes.
• The cache is keyed by MCP session ID. Concurrent calls in the same session deduplicate to a single load.
• Each endpoint loads independently — a failure in one (e.g. contentTypes) yields an empty array for that global, but the others still populate.
• Auth is handled by the main thread; the loader uses the same authenticated api adapter as execute.

Known limitations

• No invalidation outside the TTL — schema or site changes made elsewhere are visible after at most 5 minutes.
• Mutations performed via execute do not refresh the cache. Re-read from the API directly when you need post-mutation state.
• Content type list is capped at 200 entries per session load.

Development#

---

Local Development Setup#

For developers who want to contribute or modify the MCP server:

1. Clone and Setup#

# Clone the dotCMS repository
git clone https://github.com/dotCMS/core.git
cd core/core-web

# Install dependencies
pnpm install

# Build the server. The build regenerates the OpenAPI spec first (via dependsOn) — by
# default from https://demo.dotcms.com; see "Building against a local dotCMS instance" below.
pnpm nx build mcp-server

[!NOTE] Files are located in core-web/apps/mcp-server (tools/config) and core-web/libs/sdk/ai (runtime primitives + spec). We use Nx monorepo.

Refreshing the OpenAPI Spec#

The processed spec lives at libs/sdk/ai/src/generated/spec.json. It is build-generated and git-ignored — the build/serve/test targets regenerate it via dependsOn, so you rarely run this by hand. The source is resolved in this order: an explicit CLI arg, then DOTCMS_SPEC_URL, then ${DOTCMS_URL}/api/openapi.json, then the demo instance.

# Defaults to https://demo.dotcms.com/api/openapi.json
pnpm nx run sdk-ai:generate-spec

# Override with a different instance — CLI arg (URL or local file path):
pnpm nx run sdk-ai:generate-spec -- http://localhost:8080/api/openapi.json
pnpm nx run sdk-ai:generate-spec -- ./openapi.json

There is nothing to commit — the spec is regenerated at build time. CI builds it from the demo instance by default.

Building against a local dotCMS instance#

The search tool exposes whatever endpoints are in the bundled spec.json, so to describe your local instance you must regenerate the spec as part of the build.

[!IMPORTANT] Don't run generate-spec and then build as two separate steps. The build target re-runs generate-spec itself (via dependsOn), and with no source set it falls back to the demo instance — overwriting the spec you just generated. Pass the source so the build's own generate-spec uses it.

Set DOTCMS_SPEC_URL — it's an environment variable, so it flows into the generate-spec task that build runs automatically (a CLI -- arg would not). One command:

# Regenerate the spec from your local instance AND build, in one step
DOTCMS_SPEC_URL=http://localhost:8080/api/openapi.json pnpm nx build mcp-server

# Then run it against the same instance (provide a local API token)
npx @modelcontextprotocol/inspector \
  -e DOTCMS_URL=http://localhost:8080 \
  -e AUTH_TOKEN=your-local-api-token \
  node dist/apps/mcp-server/stdio.js

[!NOTE] The spec source (what search describes) and DOTCMS_URL (where the tools send requests at runtime) are separate. Point them at the same instance so the spec matches what the API serves. If DOTCMS_URL is already exported in your shell, generate-spec will reuse it (${DOTCMS_URL}/api/openapi.json) and you can drop DOTCMS_SPEC_URL entirely.

2. Use MCP Inspector for debug#

After a successful build:

npx @modelcontextprotocol/inspector -e DOTCMS_URL=https://demo.dotcms.com -e AUTH_TOKEN=the-api-token node dist/apps/mcp-server/stdio.js

3. Use Local Build in AI Assistants#

The built server works with both node and bun — the correct sandbox is selected automatically.

Using Node.js:

{
    "mcpServers": {
        "dotcms": {
            "command": "node",
            "args": ["/path/to/dotcms/core/core-web/dist/apps/mcp-server/stdio.js"],
            "env": {
                "DOTCMS_URL": "your-dotcms-url",
                "AUTH_TOKEN": "your-api-token"
            }
        }
    }
}

Using Bun:

{
    "mcpServers": {
        "dotcms": {
            "command": "bun",
            "args": ["/path/to/dotcms/core/core-web/dist/apps/mcp-server/stdio.js"],
            "env": {
                "DOTCMS_URL": "your-dotcms-url",
                "AUTH_TOKEN": "your-api-token"
            }
        }
    }
}

Project Structure#

apps/mcp-server/                         # MCP server (thin xmcp wrappers)
├── src/
│   ├── tools/
│   │   ├── search.ts       # API spec exploration tool
│   │   ├── execute.ts      # API execution tool
│   │   ├── download_assets.ts
│   │   └── upload_assets.ts
│   ├── lib/
│   │   └── assets-transfer.ts
│   └── prompts/            # Prompt templates (xmcp convention)
├── xmcp.config.ts          # xmcp bundler configuration
├── jest.config.ts          # Test configuration
└── project.json            # Nx project configuration

libs/sdk/ai/                      # Portable runtime primitives
├── scripts/
│   └── generate-spec.ts    # OpenAPI spec processor (run manually to refresh)
├── src/
│   ├── lib/
│   │   ├── executor.ts     # Sandbox executor orchestration
│   │   ├── http-client.ts  # Authenticated HTTP adapter
│   │   ├── spec.ts         # OpenAPI spec loader
│   │   ├── types.ts        # TypeScript type definitions
│   │   └── sandbox/        # Sandbox isolation (dual-runtime)
│   │       ├── index.ts        # Runtime detection factory
│   │       ├── interface.ts    # Sandbox interface
│   │       ├── bun-worker.ts   # Bun Web Worker sandbox
│   │       └── node-worker.ts  # Node.js worker_threads sandbox
│   └── generated/
│       └── spec.json       # Committed processed OpenAPI spec
└── project.json            # Nx project configuration

Key Architecture Patterns#

xmcp Framework: The server uses xmcp for MCP protocol handling:

• Tools are auto-discovered from src/tools/
• Each tool exports schema, metadata, and a default handler function
• Built with rspack for optimized bundling

Sandbox Isolation: Code execution is sandboxed using Workers with dual-runtime support:

• Bun: Uses native Web Workers (Blob + URL.createObjectURL)
• Node.js: Uses worker_threads (new Worker(code, { eval: true }))
• Runtime is detected automatically via typeof globalThis.Bun
• API tokens are never exposed to sandbox code
• Configurable timeout prevents runaway execution
• Adapter pattern bridges sandbox ↔ main thread for API calls

Build-time Spec Processing: The OpenAPI spec is pre-processed at build time:

• generate-spec target dereferences $ref pointers and filters to relevant endpoints
• Output is a compact JSON embedded in the bundle
• Reduces runtime overhead and MCP response size

Development Commands#

# Build for production (regenerates the spec from demo by default; see local-build section)
pnpm nx build mcp-server

# Development mode (with hot reload)
pnpm nx serve mcp-server

# Lint the code
pnpm nx lint mcp-server

# Run all tests
pnpm nx test mcp-server

# Run tests in watch mode
pnpm nx test mcp-server --watch

# Refresh the OpenAPI spec (run when dotCMS API changes, then commit spec.json)
# Defaults to https://demo.dotcms.com/api/openapi.json
pnpm nx run sdk-ai:generate-spec

Contributing Guidelines#

When adding new MCP tools:

1. Create a new .ts file in src/tools/
2. Export schema (Zod), metadata (ToolMetadata), and a default handler
3. xmcp auto-discovers the tool — no registration needed
4. Add tests and documentation

Security Best Practices#

---

API Token Security#

• Principle of Least Privilege: Only grant permissions required for your use case
• Environment Variables: Never hardcode tokens in source code
• Token Rotation: Regularly rotate API tokens
• Monitoring: Monitor API usage for unusual patterns
• HTTPS Only: Always use HTTPS for dotCMS connections
• Sandbox Isolation: API tokens are injected by the main thread and never exposed to sandbox code

dotCMS Support#

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We offer multiple channels to get help with the dotCMS MCP Server:

• GitHub Issues: For bug reports and feature requests, please open an issue in the GitHub repository
• Community Forum: Join our community discussions to ask questions and share solutions
• Documentation: Visit our developer documentation for detailed guides

When reporting issues, please include:

• MCP server version and build information
• dotCMS version and environment details
• AI assistant being used (Claude, Cursor, etc.)
• Minimal reproduction steps
• Expected vs. actual behavior
• Relevant log output

How To Contribute#

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GitHub pull requests are the preferred method to contribute code to dotCMS. We welcome contributions to the dotCMS MCP Server! If you'd like to contribute, please follow these steps:

1. Fork the repository dotCMS/core
2. Create a feature branch (git checkout -b feature/amazing-mcp-feature)
3. Make your changes in the apps/mcp-server directory
4. Add tests for new functionality
5. Run the test suite (pnpm nx test mcp-server)
6. Commit your changes (git commit -m 'Add amazing MCP feature')
7. Push to the branch (git push origin feature/amazing-mcp-feature)
8. Open a Pull Request

Licensing Information#

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dotCMS is available under either the Business Source License 1.1 (BSL) or a commercial license.

Under the BSL, dotCMS can be used at no cost by individual developers, small businesses or agencies under $5M in total finances, and by larger organizations in non-production environments. Every BSL release automatically converts to GPL v3 four years after its release date. For full terms and FAQs, visit dotcms.com/bsl and dotcms.com/bsl-faq.

Production use in larger organizations, along with access to managed cloud, SLAs, support, and enterprise capabilities, is available under a commercial license from dotCMS. For details on commercial plans, features, and support options, see dotcms.com/pricing.